
'''simple docstring'''







from importlib import import_module

from .logging import get_logger


lowercase       :				Tuple =   get_logger(__name__)


class 		__UpperCAmelCase :


							def __init__(			self       ,  lowerCAmelCase_       ,  lowerCAmelCase_=None    ):





								"""simple docstring"""






								_snake_case  		=						attrs or []
								if module is not None:
									for key in module.__dict__:
										if key in attrs or not key.startswith('__'    ):
											setattr(self       ,  lowerCAmelCase_       ,  getattr(lowerCAmelCase_       ,  lowerCAmelCase_    )    )
								_snake_case  		=						module._original_module if isinstance(lowerCAmelCase_       ,  _PatchedModuleObj    ) else module


class 		__UpperCAmelCase :
							__lowercase 						=			[]


							def __init__(			self       ,  lowerCAmelCase_       ,  lowerCAmelCase_       ,  lowerCAmelCase_       ,  lowerCAmelCase_=None    ):





								"""simple docstring"""






								_snake_case  		=						obj
								_snake_case  		=						target
								_snake_case  		=						new
								_snake_case  		=						target.split('.'    )[0]
								_snake_case  		=						{}
								_snake_case  		=						attrs or []


							def __enter__(			self    ):





								"""simple docstring"""






								*_snake_case		,					_snake_case  		=						self.target.split('.'    )

								# Patch modules:
								# it's used to patch attributes of submodules like "os.path.join";
								# in this case we need to patch "os" and "os.path"

								for i in range(len(lowerCAmelCase_    )    ):
									try:
										_snake_case  		=						import_module('.'.join(submodules[: i + 1]    )    )
									except ModuleNotFoundError:
										continue
									# We iterate over all the globals in self.obj in case we find "os" or "os.path"
									for attr in self.obj.__dir__():
										_snake_case  		=						getattr(self.obj       ,  lowerCAmelCase_    )
										# We don't check for the name of the global, but rather if its value *is* "os" or "os.path".
										# This allows to patch renamed modules like "from os import path as ospath".
										if obj_attr is submodule or (
										    (isinstance(lowerCAmelCase_       ,  _PatchedModuleObj    ) and obj_attr._original_module is submodule)
										):
											_snake_case  		=						obj_attr
											# patch at top level
											setattr(self.obj       ,  lowerCAmelCase_       ,  _PatchedModuleObj(lowerCAmelCase_       ,  attrs=self.attrs    )    )
											_snake_case  		=						getattr(self.obj       ,  lowerCAmelCase_    )
											# construct lower levels patches
											for key in submodules[i + 1 :]:
												setattr(lowerCAmelCase_       ,  lowerCAmelCase_       ,  _PatchedModuleObj(getattr(lowerCAmelCase_       ,  lowerCAmelCase_       ,  lowerCAmelCase_    )       ,  attrs=self.attrs    )    )
												_snake_case  		=						getattr(lowerCAmelCase_       ,  lowerCAmelCase_    )
											# finally set the target attribute
											setattr(lowerCAmelCase_       ,  lowerCAmelCase_       ,  self.new    )

        # Patch attribute itself:
        # it's used for builtins like "open",
        # and also to patch "os.path.join" we may also need to patch "join"
        # itself if it was imported as "from os.path import join".

								if submodules:  # if it's an attribute of a submodule like "os.path.join"
									try:
										_snake_case  		=						getattr(import_module('.'.join(lowerCAmelCase_    )    )       ,  lowerCAmelCase_    )
									except (AttributeError, ModuleNotFoundError):
										return
									# We iterate over all the globals in self.obj in case we find "os.path.join"
									for attr in self.obj.__dir__():
										# We don't check for the name of the global, but rather if its value *is* "os.path.join".
										# This allows to patch renamed attributes like "from os.path import join as pjoin".
										if getattr(self.obj       ,  lowerCAmelCase_    ) is attr_value:
											_snake_case  		=						getattr(self.obj       ,  lowerCAmelCase_    )
											setattr(self.obj       ,  lowerCAmelCase_       ,  self.new    )
								elif target_attr in globals()["__builtins__"]:  # if it'a s builtin like "open"
									_snake_case  		=						globals()['__builtins__'][target_attr]
									setattr(self.obj       ,  lowerCAmelCase_       ,  self.new    )
								else:
									raise RuntimeError(F'Tried to patch attribute {target_attr} instead of a submodule.'    )


							def __exit__(			self       ,  *lowerCAmelCase_    ):





								"""simple docstring"""






								for attr in list(self.original    ):
									setattr(self.obj       ,  lowerCAmelCase_       ,  self.original.pop(lowerCAmelCase_    )    )


							def 					lowerCamelCase							(			self    ):





								"""simple docstring"""






								self.__enter__()
								self._active_patches.append(self    )




							def 					lowerCamelCase							(			self    ):





								"""simple docstring"""






								try:
									self._active_patches.remove(self    )
								except ValueError:
									# If the patch hasn't been started this will fail
									return None

								return self.__exit__()








"""simple docstring"""





import unittest

import numpy as np
import torch

from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()

class 						lowercase   (   unittest.TestCase   ):





      @property
      def        _snake_case     (			self					)						->	List[str]:
            torch.manual_seed(0					)
            lowerCAmelCase    		=			UNetaDModel(
                block_out_channels=(32, 64) ,		layers_per_block=2 ,		sample_size=32 ,		in_channels=3 ,		out_channels=3 ,		down_block_types=("""DownBlock2D""", """AttnDownBlock2D""") ,		up_block_types=("""AttnUpBlock2D""", """UpBlock2D""") ,		)
            return model





      def        _snake_case     (			self					)						->	List[Any]:
            lowerCAmelCase    		=			self.dummy_uncond_unet
            lowerCAmelCase    		=			ScoreSdeVeScheduler()

            lowerCAmelCase    		=			ScoreSdeVePipeline(unet=lowercase ,		scheduler=lowercase					)
            sde_ve.to(lowercase					)
            sde_ve.set_progress_bar_config(disable=lowercase					)

            lowerCAmelCase    		=			torch.manual_seed(0					)
            lowerCAmelCase    		=			sde_ve(num_inference_steps=2 ,		output_type="""numpy""" ,		generator=lowercase					).images

            lowerCAmelCase    		=			torch.manual_seed(0					)
            lowerCAmelCase    		=			sde_ve(num_inference_steps=2 ,		output_type="""numpy""" ,		generator=lowercase ,		return_dict=lowercase					)[
                0
            ]

            lowerCAmelCase    		=			image[0, -3:, -3:, -1]
            lowerCAmelCase    		=			image_from_tuple[0, -3:, -3:, -1]

            assert image.shape == (1, 32, 32, 3)
            lowerCAmelCase    		=			np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]					)

            assert np.abs(image_slice.flatten() - expected_slice					).max() < 1e-2
            assert np.abs(image_from_tuple_slice.flatten() - expected_slice					).max() < 1e-2







@slow
@require_torch
class 						lowercase   (   unittest.TestCase   ):





      def        _snake_case     (			self					)						->	Optional[int]:
            lowerCAmelCase    		=			"""google/ncsnpp-church-256"""
            lowerCAmelCase    		=			UNetaDModel.from_pretrained(lowercase					)

            lowerCAmelCase    		=			ScoreSdeVeScheduler.from_pretrained(lowercase					)

            lowerCAmelCase    		=			ScoreSdeVePipeline(unet=lowercase ,		scheduler=lowercase					)
            sde_ve.to(lowercase					)
            sde_ve.set_progress_bar_config(disable=lowercase					)

            lowerCAmelCase    		=			torch.manual_seed(0					)
            lowerCAmelCase    		=			sde_ve(num_inference_steps=10 ,		output_type="""numpy""" ,		generator=lowercase					).images

            lowerCAmelCase    		=			image[0, -3:, -3:, -1]

            assert image.shape == (1, 256, 256, 3)

            lowerCAmelCase    		=			np.array([0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0]					)

            assert np.abs(image_slice.flatten() - expected_slice					).max() < 1e-2






